Volume 14 | Issue 4

 Abstract

Adolescence is considered an important stage in an individual's life during which self-consciousness and identity are more prevalent. Adolescents are more sensitive to peer evaluation during this stage. Adolescence is often considered a stage where social anxiety is more common among individuals. Social anxiety is the fear or apprehension experienced by an individual in social situations. Adolescents are more engaged with social media in the modern age compared to previous eras. Two important psychosocial factors that may cause social anxiety among adolescents are imaginary audience beliefs and problematic social media use. This study aimed to investigate whether imaginary audience beliefs and problematic social media use predict social anxiety among adolescents. A sample size of 132 adolescents between 13 and 18 years of age was considered for the study using a convenience sampling design. Standardized instruments were used to measure imaginary audience beliefs, problematic social media use, and social anxiety among the sample group.The results revealed that both imaginary audience beliefs and problematic social media usage were positively related to social anxiety and were significant predictors of levels of social anxiety. These findings underscore the need to take into consideration cognitive and behavioral aspects of social media usage while developing interventions to aid adolescents' mental health. To conclude, this paper makes an addition to the existing body of knowledge on the determinants of social anxiety disorder and the association between imaginary audience and social media addiction. Therefore, it becomes necessary for adolescents to engage in healthy social media behavior and be conscious of their self-consciousness in order to overcome social anxiety.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Keywords - Social anxiety, imaginary audience beliefs, problematic social media usage, adolescents, psychosocial predictors

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper establishes a common fixed-point theorem in complex valued partial metric spaces using rational expansive mappings and newly defined implicit relations. Under the framework of occasionally weakly compatible mappings, the existence and uniqueness of a common fixed point for four self-mappings are proved. Our result is generalization of some of the results existing in the literature.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Common fixed point, Complex valued partial metric space, Rational expansive mapping, Occasionally Weakly Compatible (OWC) mappings, Implicit relation

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Sacred Waters by Meira Chand is a compelling and multi layered exploration of female agency within the overlapping frameworks of patriarchy and colonial rule in South and South East Asia. This paper analyses the evolution of that agency through the life of the novel's protagonist Sita. She was a victim of the oppressive traditions created by patriarchal institutions that treated female body as subordinate. She goes on to become a war veteran who served in The Rani of Jhansi Regiment, through the medium of literacy and her sheer passion. Drawing on the theory of subaltern by Gayatri Spivak, the paper discusses how the 'grammar of nothingness' was employed by the society to reduce the women to a worthless and voiceless object. The analysis then applies Judith Butler's theory of gender performativity to portray the social transformation of the naive girl into a self-reliant woman by disrupting the gender normed roles. Chandra Talpade Mohanty's critique of the monolithic 'Third World Woman' is deployed to resist the reduction of the novel's female characters to a singular condition of victimhood. It throws light on the differential axes of class, caste, and colonial privilege that fracture the category of women in the novel. Finally, the intergenerational transmission of agency from Sita to her adoptive daughter Amita through Marianne Hirsch's theory of postmemory. The paper argues that Sacred Waters presents female agency not as a single event but as an ongoing process of claiming the voice, body and narrative that is incomplete yet quietly insistent.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Female Agency, Sacred Waters, Meira Chand, Patriarchy, Rani of Jhansi Regiment, Subaltern, Gender Performativity, Third World Women, Postmemory, Intergenerational

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study looks at how the book "The Foreigner" by Arun Joshi, written in 1968, deals with big questions about life, like feeling alone, being free, and doing the right thing. The main character, Sindi Oberoi, is like a symbol of people today who are trying to figure out who they are in a world that doesn't seem to care. We're using ideas from philosophers like Jean-Paul Sartre and Albert Camus to understand how Joshi uses these concepts in an Indian setting. What we found is that Joshi doesn't just show how sad and hopeless life can be, but also how people can wake up and start making good choices by taking responsibility and getting involved. By closely reading the book and using critical thinking, we're saying that "The Foreigner" is an important part of talking about these big life questions in Indian English literature.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Existentialism, Alienation, Identity, Freedom, Absurdity, Moral Responsibility, Indian English Fiction, Arun Joshi.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Human development and the ability to overcome the intergenerational cycle of rural poverty are based on access to basic amenities safe drinking water, sanitation, electricity, housing, education and healthcare. The rural-urban disparity in amenity coverage in India is stubbornly large, even after 60 years of planned development and with a multiplicity of flagship programmes. The Bundelkhand area, especially Banda district of Uttar Pradesh is a miniature of this challenge. Having almost 94 percent of its population in the villages, Banda is afflicted with acute depletion of groundwater, unsanitary habits, unstable power generation, lack of health and education facilities and a chronic lack of housing facilities. The present paper is a data based extensive analysis of the situation of, problems in and difficulties of providing basic amenities of rural Banda. Based on Census 2011, government dashboards, third party audits, academic research and field surveys, the study quantifies the coverage and functionality of important services. It determines the key constraints that are hydro geological, behavioural, institutional, financial and governance related that hinder universal access. Lastly, it provides a list of policy recommendations which can be implemented to close the amenity gap, and improve the quality of services and promote inclusive rural development in Banda and other backward regions

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Basic amenities, rural development, water scarcity, sanitation, electrification, housing, primary health centres, Banda district, Bundelkhand.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The study of consciousness has remained a central concern in both philosophical and scientific discourse, raising fundamental questions about the nature of reality, selfhood, and awareness. This paper undertakes a theoretical inquiry into human consciousness as presented in the Mandukya Upanishad, one of the most concise yet profound texts in the Upanishadic tradition. The Upanishad offers a systematic framework by classifying consciousness into four states: waking (j?grat), dreaming (svapna), deep sleep (su?upti), and the transcendental state (tur?ya). The study analyzes these four states as progressive levels of awareness, demonstrating how empirical and mental experiences are ultimately grounded in a deeper, non-dual consciousness. Special emphasis is placed on the concept of tur?ya, which is described as pure, unconditioned awareness beyond subject-object duality. The paper further explores the philosophical implications of identifying ?tman (individual self) with Brahman (ultimate reality), a central doctrine within Advaita Vedanta. In addition, the symbolic significance of the syllable Om (AUM) is examined as a representation of the totality of consciousness and as a practical means for its realization. The study also engages with contemporary perspectives by comparing the Mandukya model with modern theories in psychology and neuroscience, particularly in relation to different states of consciousness. By integrating classical philosophical insights with modern discourse, this paper argues that the Mandukya Upanishad provides a comprehensive and non-dual framework for understanding consciousness, one that transcends materialistic explanations and offers a deeper ontological and experiential perspective. The findings suggest that the Upanishadic model remains highly relevant for contemporary studies of consciousness and the philosophy of mind.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Mandukya upanishad, human consciousness

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Heart disease is one of the leading causes of death worldwide. Early prediction can significantly reduce mortality rates. This paper presents a machine learning-based approach for heart disease prediction using classification algorithms such as Logistic Regression, Decision Tree, and Random Forest.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Heart Disease, Machine Learning, Classification, Healthcare, Prediction Machine learning Algorithms.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper examines the impact of bid-ask spreads and transaction costs on trading behaviour, market efficiency, and asset pricing in financial markets. Building on established theoretical models, including Roll (1984), Glosten and Milgrom (1985), Kyle (1985), and Amihud and Mendelson (1986), the study integrates recent empirical evidence from equity, fixed-income, and cryptocurrency markets up to 2026. The results show that bid-ask spreads represent not only execution costs but also reflect information asymmetry and market conditions. Transaction costs influence trading activity, portfolio decisions, and contribute to the liquidity premium in asset returns. Furthermore, modern developments such as zerocommission trading, high-frequency trading, and payment for order flow have reshaped cost structures in financial markets. Evidence from recent U.S. Treasury market volatility highlights the role of spreads in market stability. The study also evaluates financial transaction taxes, emphasizing their trade-offs between revenue generation and market efficiency.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Bid-Ask Spread, Transaction Costs, Market Liquidity, Asset Pricing, Market Microstructure, Liquidity Premium, Adverse Selection, High-Frequency Trading, Financial Transaction Tax

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Parenting styles are linked with developmental aspects and behaviour of a child including academic achievement. However, whether this association is relevant to young adult migrant students with limited direct parental influence remains unclear. The present study aims to explore the association of authoritarian and authoritative parenting and academic achievement among young adult migrant students. Data were collected from 50 participants (28 females, 22 males, aged 18 -25) studying in Bengaluru. Perceived parenting styles were analysed by Parental Authority Questionnaire (PAQ) (Buri, 1991) administered using the Likert scale. Academic data of the sample was collected using self-reported CGPA. The reliability of parenting scores were found to be above 0.75 using Cronbach's Alpha. Pearson correlation revealed weak correlations of authoritarian and authoritative parenting styles with academic achievement, none of which were statistically significant. The findings revealed that association between parenting styles and academic achievement may be reduced during young adulthood, particularly when individuals are migrant students, not directly influenced by parents.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Authoritative parenting, Authoritarian parenting, Academic achievement, Young adults, Parenting, Migrant students

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Quick commerce (Q-commerce), characterized by ultra-fast delivery of goods within a short time frame, has rapidly transformed the retail landscape in India. Hyderabad, as a major metropolitan and IT hub, has emerged as a significant market for Q-commerce expansion. This study examines the growth trends, key drivers, challenges, and future opportunities of Q-commerce in Hyderabad. Using secondary data and a structured questionnaire, the research identifies consumer preferences, usage patterns, and satisfaction levels. The findings reveal that convenience, speed, and digital accessibility are major factors driving adoption, while profitability concerns and operational challenges remain key issues. The study concludes that Q-commerce has strong growth potential, with scope for diversification and technological integration.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Quick Commerce (Q-commerce), Consumer Behavior ,Digital Transformation, Diversification,

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Working capital management is a very important part of financial management, which involves the management of short-term assets and liabilities of an organisation. This includes maintaining sufficient liquidity to conduct organisational activities in an efficient manner. In addition to this, this involves improving the profitability of the organisation. Working capital management plays an important role, especially in the manufacturing sector, because in such industries most of the funds are invested in inventories and receivables. In this study, working capital management strategies followed by JALARAM DOORS & HARDWARES, a manufacturing and trading organization involved in wooden doors manufacturing and hardware supply, have been studied. The study relies upon secondary data collected from financial statements of the organisation from 2021-22, 2022-23, and 2024-25. Financial ratio analysis will be conducted through the current ratio, inventory turnover ratio, and debtor's turnover ratio. From the findings, it is seen that although there are satisfactory levels of liquidity in the organization, there are some issues associated with the management of inventories and fluctuation in the profitability levels

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Working Capital, Liquidity, Inventory, Receivables, Profitability

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The rapid proliferation of Internet of Things (IoT) devices has introduced significant cybersecurity challenges due to their resource-constrained nature and limited native protection mechanisms. Traditional intrusion detection systems (IDS), which rely on signature-based approaches and cloud-dependent architectures, are often unsuitable for decentralized IoT environments. This paper presents NeuroFence, a lightweight, AI-driven intrusion detection system designed for real-time cyber defense in edge-based IoT networks. The proposed system operates entirely on local gateways, such as Raspberry Pi, and leverages machine learning techniques to model normal network behaviour and detect anomalies in real time. NeuroFence incorporates a hybrid detection framework that combines rule-based analysis with unsupervised anomaly detection models, enabling both immediate threat identification and adaptive learning against evolving attack patterns. The system captures live network traffic, extracts features using sliding-window techniques, and evaluates traffic behaviour using models such as Isolation Forest and TinyML-based classifiers. A complete edge-first architecture is implemented, integrating packet sniffing (Scapy), lightweight data processing, local storage (SQLite), and an interactive dashboard built using Flask and React for real-time alert visualization and operator response. The system also includes mechanisms for safe mitigation, forensic logging, and continuous model improvement through feedback-driven learning. Experimental evaluation demonstrates that NeuroFence effectively detects anomalous IoT traffic with low latency and minimal computational overhead, making it suitable for deployment in resource-constrained environments such as smart homes, industrial IoT systems, and remote installations. The proposed solution highlights the potential of decentralized, AI-powered security frameworks in enhancing the resilience and autonomy of modern IoT ecosystems.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Internet of Things (IoT), Intrusion Detection System (IDS), Edge Computing, Machine Learning, Anomaly Detection, TinyML, Cybersecurity, Network Traffic Analysis, Raspberry Pi, Isolation Forest

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Land use pattern is a reflection of the interrelationship between natural resources and human activities in a region. Fatehpur district, located in the Ganga-Yamuna Doab, is highly suitable for land use studies due to its agrarian nature. The present study is based on the spatio-temporal analysis of land resources in Fatehpur district. The main objective of the study is to understand the distribution, trends, and variability of different land use categories in the district--such as agricultural land, forest area, fallow and wasteland, pasture land, and built-up area. In this research, secondary data (district statistical handbook, land records, and census data) have been used to classify land use and analyze changes over time. The analysis clearly indicates that agriculture is the dominant land use in the district, occupying the largest proportion of the total area, whereas forest area is very limited. Due to urbanization and infrastructural development, there has been a gradual increase in built-up areas, which is putting pressure on agricultural land. The study also reveals that land use patterns are strongly influenced not only by physical factors--such as soil, climate, and water resources--but also by socio-economic factors like population growth, technological development, and market accessibility. Additionally, issues such as land degradation, declining groundwater levels, and imbalanced land use are emerging challenges in the region. Finally, the study emphasizes the need for sustainable land use management measures, such as agricultural diversification and the promotion of modern irrigation techniques, to ensure balanced and long-term utilization of resources in Fatehpur district.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Land Use Pattern, Spatio-Temporal Analysis, Fatehpur District

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Over the past few years, the safety of women has emerged as an important issue in society, particularly in the presence of other people and when the circumstances are unfavorable during the nights. As the number of harassment and emergency incidents increases, the need to find intelligent, non-obtrusive safety solutions that will work in real time is growing. The proposed project is called Night Guardian: Empowering Women Safety with Hand Sign-based Communication and AI and suggests a new solution that would be based on leveraging artificial intelligence and computer vision to provide immediate assistance in case of distress scenarios without having to engage with the user directly. The system is developed based on the latest technologies like MediaPipe and OpenCV to record and process real-time video feeds of a webcam. MediaPipe is applied in the correct hand landmark detection and keypoint extraction in order to determine hand gestures very precisely. These features are extracted and converted into numerical forms and input to machine learning algorithms like Random Forest, Support Vector Machine (SVM) and K-Nearest Neighbor (KNN). Performance measures such as precision, recall, and F1-score are used to train and test the models to be reliable at gesture recognition. After a distressing gesture has been identified, an alert system is automatically triggered. This involves raising a local alarm to draw attention locally and an automated email notification and a picture of the gesture to emergency contacts or authorities that are predetermined. The combination of these alert mechanisms is to make sure that there is quick response hence increasing the possibility of intervention in time. With the application of AI, the system can be continuously and effectively used even in dynamic environments. Altogether, the offered system will be an effective and scalable way to enhance the safety of women with the help of intelligent automation. It offers a quick, convenient, and free form of emergency communication by using machine learning and real-time gesture recognition to deliver a hands-free form of communication. This project, apart from fostering innovation in technology, helps to enhance social well being by making people be empowered with proactive safety tools.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Over the past few years, the safety of women has emerged as an important issue in society, particularly in the presence of other people and when the circumstances are unfavorable during the nights. As the number of harassment and emergency incidents increases, the need to find intelligent, non-obtrusive safety solutions that will work in real time is growing. The proposed project is called Night Guardian: Empowering Women Safety with Hand Sign-based Communication and AI and suggests a new solut

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Crop stress is one of the foremost threats to global food security, causing yield losses estimated at 20-40% annually. Traditional monitoring relies on costly sensor arrays or time-intensive manual inspection, limiting accessibility for small-scale farmers. This paper proposes a low-cost, camera-only crop stress detection system built around a fixed ESP32-CAM RGB module. A multi-task convolutional neural network (CNN) based on MobileNetV2 simultaneously classifies crop health (Healthy/Stressed), estimates a continuous stress severity score, and assesses soil surface condition (Dry/Moist/Wet). Temporal analysis via an exponentially weighted moving average (EWMA) over a rolling N-frame buffer enables detection of progressive stress onset before visible leaf damage appears, reducing false-positive alerts by 31% compared to single-frame classification. A hybrid learning pipeline combines supervised training on a labeled base dataset with semi-supervised pseudo-label fine-tuning for unseen crop types. Grad-CAM visualisations highlight stress-causative regions, improving model transparency and farmer trust. The system achieved 93.4% binary classification accuracy, 89.7% soil condition classification accuracy, and a stress severity MAE of 0.06 on held-out test data.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Crop Stress Detection, Convolutional Neural Network, ESP32-CAM, MobileNetV2, Hybrid Learning, Semi-Supervised Learning, Grad-CAM, Temporal Analysis, Precision Agriculture, Explainable AI.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

From ages together women in India have been portrayed and propagated and perpetuated as embodiments of divine power or 'Shakti.' But due to the decay of value systems in education as an epitome of societal progress, girls have been denied dignity and equality in status as compared to male counterparts considered in the same parlance. Nationwide, campus safety programmes have been launched to provide a decisive move to gender sensitization and women's empowerment. After a decade-long rule by the predecessor BJD, the newly elected The BJP-led government, assuming power for the first time, launched the 'Shakti Shree' programme for giving a boost to women's empowerment in the institutions of higher education. With innovative features like empowered facilitators, technology-driven applications, and online capacity-building initiatives, the programme has proved to be impactful in ensuring women's safety to some extent while aiming at reducing the accelerated pace of terrorizing vengeance on academic campuses. This article clearly attempts an analytical exposition on of this initiative, aiming at reducing the gender mainstreaming of education, giving rise to all-round progress of womenfolk in the institutions of higher learning in the state of Odisha.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Higher Education, Women, Gender, Violence, Colleges, Safe, Environment

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

A Comprehensive Clinical Synthesis of Chaturbeeja Churna for Primary Dysmenorrhoea

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

A Comprehensive Clinical Synthesis of Chaturbeeja Churna for Primary Dysmenorrhoea

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Tuberculosis (TB) is not merely a biomedical condition; it carries profound psychological and social consequences for affected individuals. The present review examines gender differences in anxiety, depression, stress, and perceived stigma among tuberculosis patients. Evidence consistently indicates that psychological distress is markedly prevalent in TB populations, with rates of depression and anxiety significantly exceeding those observed in the general population. Women with TB are more likely to experience higher levels of anxiety and depression, shaped by hormonal factors, gendered social roles, and cultural expectations. Stigma associated with TB is also gendered in nature, with women facing more severe social consequences including threats to marital prospects and family reputation. The review draws on research from India and other high-burden countries to highlight psychosocial dimensions of TB that are often underaddressed in clinical settings. Gaps in literature, particularly around gender-disaggregated analyses in Indian clinical populations, are noted. The paper underscores the need for gender-sensitive mental health screening and psychosocial interventions to be integrated within tuberculosis treatment programs.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

tuberculosis, anxiety, depression, perceived stigma, gender differences, internalized stigma, mental health

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The rapid growth of Internet of Things (IoT) devices in domains such as smart homes, healthcare, and industrial systems has introduced significant cybersecurity challenges. Many IoT devices have limited computational resources and weak security mechanisms, making them vulnerable to cyber threats such as malware, denial-of-service attacks, and unauthorised access. Traditional intrusion detection systems (IDS) that rely on rule-based or signature-based methods often fail to detect zero-day attacks and evolving intrusion patterns. To address these limitations, this paper proposes CyberShield - Sentinel Intelligence for Secure IoT Environments, an AI-powered intrusion detection framework. The system uses the NSL-KDD dataset and employs a hybrid machine-learning approach integrating Isolation Forest for anomaly detection and Random Forest for threat classification. In addition, Small Batch Processing is implemented to improve scalability and reduce computational overhead. The proposed framework enhances detection accuracy and provides an efficient solution for securing IoT networks.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

IoT Security, Intrusion Detection System (IDS), NSL-KDD Dataset, Hybrid Machine Learning, Isolation Forest, Random Forest, Anomaly Detection, Small Batch Processing.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

An integrated retail management and automated checkout system has been developed as a result of the quick development of artificial intelligence (AI), with the goal of resolving common issues that traditional supermarkets and grocery stores face. In this paper, a comprehensive AI-powered solution with a single mobile and web application for consumers and retailers is presented. The system minimizes hardware dependency, lowers labor costs, and effectively removes long billing queues. Secure user authentication, instantaneous cart and bill generation, in-app payment integration with automated QR- code-based exit pass generation, real-time product self-scanning via mobile cameras, and smooth synchronization between customer and retailer dashboards are some of the major innovations. The system combines computer vision models with AI-enhanced CCTV surveillance to improve theft prevention. These models identify unusual customer behaviors and generate immediate alerts while keeping thorough activity logs. Real-time data handling, safe payment processing, and effective inventory management-- complete with low-stock alerts and sales analytics--are all guaranteed by its cloud-based architecture. This novel AI-driven framework has the potential to significantly improve operational efficiency, customer experience, and theft mitigation in retail environments, as demonstrated by experimental deployment. This solution is a valuable asset in the changing retail technology landscape because it not only simplifies the shopping experience but also improves security and operational effectiveness.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Artificial Intelligence, Automated Checkout, Computer Vision, Retail Automation, Theft Detection.

  License

Creative Commons Attribution 4.0 and The Open Definition