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Zero-DCE++Inspired Object Detection in Less Illuminated Environment Using Improved YOLOv5

Computers, Materials & Continua 2023年第12期77卷 2751-2769页

作者： Ananthakrishnan Balasundaram anshuman mohanty Ayesha Shaik Krishnadoss Pradeep Kedalu Poornachary Vijayakumar Muthu Subash Kavitha Centre for Cyber Physical Systems Vellore Institute of Technology(VIT)ChennaiTamil Nadu600127India School of Computer Science and Engineering Vellore Institute of Technology(VIT)ChennaiTamil Nadu600127India School of Information and Data Sciences Nagasaki UniversityNagasaki8528521Japan

Automated object detection has received the most attention over the *** cases ranging from autonomous driving applications to military surveillance systems,require robust detection of objects in different illumination ***-of-the-art object detectors tend to fare well in object detection during daytime ***,their performance is severely hampered in night light conditions due to poor *** address this challenge,the manuscript proposes an improved YOLOv5-based object detection framework for effective detection in unevenly illuminated nighttime ***,the preprocessing strategies involve using the Zero-DCE++approach to enhance lowlight *** is followed by optimizing the existing YOLOv5 architecture by integrating the Convolutional Block Attention Module(CBAM)in the backbone network to boost model learning capability and Depthwise Convolutional module(DWConv)in the neck network for efficient compression of network *** Night Object Detection(NOD)and Exclusively Dark(ExDARK)dataset has been used for this *** proposed framework detects classes like humans,bicycles,and *** demonstrate that the proposed architecture achieved a higher Mean Average Precision(mAP)along with a reduction in model size and total parameters,*** proposed model is lighter by 11.24%in terms of model size and 12.38%in terms of parameters when compared to baseline YOLOv5.

关键词： Object detection deep learning nighttime road scenes YOLOv5 DWConv Zero-DCE++ CBAM

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Carbon and water footprints of major crop production in India

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Pedosphere 2023年第3期33卷 448-462页

作者： Amaresh Kumar NAYAK Rahul TRIPATHI Manish DEBNATH Chinmaya Kumar SWAIN Biswaranjan DHAL Shanmugam VIJAYKUMAR anshuman Debasis NAYAK Sangita mohanty Mohammad SHAHID Anjani KUMAR Manoj RAJAK Khitish Chandra MOHARANA Dibyendu CHATTERJEE Susmita MUNDA Pravat GURU Rubina KHANAM Banwari LAL Priyanka GAUTAM Suschismita PATTANAIK Arvind Kumar SHUKLA Nuala FITTON Pete SMITH Himanshu PATHAK Indian Council of Agriculture Research(ICAR)-National Rice Research Institute Cuttack 753006(India) ICAR-Central Sheep and Wool Research Institute Avikanagar 304501(India) ICAR-National Research Centre on Camel Bikaner 304001(India) ICAR-Indian Institute of Soil Science Bhopal 462038(India) Institute of Biological and Environmental Sciences University of Aberdeen23St Machar DriveAberdeen AB243UU(UK)

Scarcity of water and emission of greenhouse gases(GHGs)are the two key environmental issues affecting crop production in *** the carbon footprint(CF)and water footprint(WF)of crop production can help to mitigate the environmental hazards that stem from GHG emissions and water *** CFs and WFs of three major cereal crops,rice,wheat,and maize,were estimated for the year 2014 under the environmental conditions in India,based on national statistics and other data *** CFs(TCFs)of rice,wheat,and maize in India were estimated to be 2.44,1.27,and 0.80 t CO_(2)equivalent ha-1,respectively,and product WFs for rice,wheat,and maize in India were 3.52,1.59,and 2.06 m3 kg^(-1),*** WF was found to be the highest in West India for rice and in South India for both wheat and maize,with the highest irrigation water use in these *** was a positive correlation between TCF and total WF,and hence mitigation of both was possibly simultaneous in various regions in *** measures for mitigating GHG emissions and optimizing water use for rice,wheat,and maize production in India are recommended in this paper.

关键词： cereal crop crop planning green water footprint greenhouse gas emission water productivity water use

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