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Vijeta Sharma, Manjari Gupta, Ajai Kumar and Deepti Mishra
The video camera is essential for reliable activity monitoring, and a robust analysis helps in efficient interpretation. The systematic assessment of classroom activity through videos can help understand engagement levels from the perspective of both stu...
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Yuhwan Kim, Chang-Ho Choi, Chang-Young Park and Seonghyun Park
In today?s society, where people spend over 90% of their time indoors, indoor air quality (IAQ) is crucial for sustaining human life. However, as various indoor activities such as cooking generate diverse types of pollutants in indoor spaces, IAQ has eme...
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Varsha S. Lalapura, Veerender Reddy Bhimavarapu, J. Amudha and Hariram Selvamurugan Satheesh
The Recurrent Neural Networks (RNNs) are an essential class of supervised learning algorithms. Complex tasks like speech recognition, machine translation, sentiment classification, weather prediction, etc., are now performed by well-trained RNNs. Local o...
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Mohamed Dhiaeddine Messaoudi, Bob-Antoine J. Menelas and Hamid Mcheick
This research introduces an innovative smart cane architecture designed to empower visually impaired individuals. Integrating advanced sensors and social media connectivity, the smart cane enhances accessibility and encourages physical activity. Three me...
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Hayat Ullah and Arslan Munir
The recognition of human activities using vision-based techniques has become a crucial research field in video analytics. Over the last decade, there have been numerous advancements in deep learning algorithms aimed at accurately detecting complex human ...
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Mohammad Shahbazi, Kamyar Mohammadi, Sayed M. Derakhshani and Peter W. G. Groot Koerkamp
Laying hen activities in modern intensive housing systems can dramatically influence the policies needed for the optimal management of such systems. Intermittent monitoring of different behaviors during daytime cannot provide a good overview, since daily...
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Yunqian Yu, Kun Tang and Yaqing Liu
Daily activity recognition between different smart home environments faces some challenges, such as an insufficient amount of data and differences in data distribution. However, a deep network requires a large amount of labeled data for training. Additio...
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Obada Issa and Tamer Shanableh
This paper proposes a novel approach to activity recognition where videos are compressed using video coding to generate feature vectors based on compression variables. We propose to eliminate the temporal domain of feature vectors by computing the mean a...
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André B. Peres, Mário C. Espada, Fernando J. Santos, Ricardo A. M. Robalo, Amândio A. P. Dias, Jesús Muñoz-Jiménez, Andrei Sancassani, Danilo A. Massini and Dalton M. Pessôa Filho
This paper presents a comparison of mathematical and cinematic motion analysis regarding the accuracy of the detection of alterations in the patterns of positional sequence during biceps-curl lifting exercise. Two different methods, one with and one with...
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Yaxin Mao, Lamei Yan, Hongyu Guo, Yujie Hong, Xiaocheng Huang and Youwei Yuan
Inertial measurement unit (IMU) technology has gained popularity in human activity recognition (HAR) due to its ability to identify human activity by measuring acceleration, angular velocity, and magnetic flux in key body areas like the wrist and knee. I...
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