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Dania Tamayo-Vera, Xiuquan Wang and Morteza Mesbah
The interplay of machine learning (ML) and deep learning (DL) within the agroclimatic domain is pivotal for addressing the multifaceted challenges posed by climate change on agriculture. This paper embarks on a systematic review to dissect the current ut...
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Dana Catalina Popa, Yolanda Laurent, Razvan Alexandru Popa, Adrian Pasat, Mihaela Balanescu, Ekaterina Svertoka, Elena Narcisa Pogurschi, Livia Vidu and Monica Paula Marin
This research introduces an innovative platform designed to manage greenhouse gas (GHG) emissions in mixed farms. Emphasizing the urgent need to address GHG emissions, particularly methane (CH4) and nitrous oxide (N2O), the platform targets mixed farming...
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Hao-Ran Qu and Wen-Hao Su
Weeds and crops engage in a relentless battle for the same resources, leading to potential reductions in crop yields and increased agricultural costs. Traditional methods of weed control, such as heavy herbicide use, come with the drawback of promoting w...
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Ruoyang Li, Shuping Xiong, Yinchao Che, Lei Shi, Xinming Ma and Lei Xi
Semantic segmentation algorithms leveraging deep convolutional neural networks often encounter challenges due to their extensive parameters, high computational complexity, and slow execution. To address these issues, we introduce a semantic segmentation ...
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Senlin Guan, Kimiyasu Takahashi, Shunichiro Watanabe and Katsunori Tanaka
The destructive impact of invasive apple snail (Pomacea canaliculata) on young rice seedlings has garnered global attention, particularly in warm regions where rice production occurs. The preventative application of insecticide, particularly in areas wit...
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Noor Fadzlinda Othman, Mohammad Effendy Ya?acob, Li Lu, Ahmad Hakiim Jamaluddin, Ahmad Suhaizi Mat Su, Hashim Hizam, Rosnah Shamsudin and Juju Nakasha Jaafar
The increasing concerns about the impact of large-scale solar photovoltaic farms on the environment and the energy crisis have raised many questions. This issue is mainly addressed by the integration of agriculture advancement in solar photovoltaic syste...
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Boyu Xie, Qi Su, Beilun Tang, Yan Li, Zhengwu Yang, Jiaoyang Wang, Chenxi Wang, Jingxian Lin and Lin Li
With the advancement in modern agricultural technologies, ensuring crop health and enhancing yield have become paramount. This study aims to address potential shortcomings in the existing chili disease detection methods, particularly the absence of optim...
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Mujahed Al-Dhaifallah, Fahad M. Al-Qahtani, Sami Elferik and Abdul-Wahid A. Saif
Quadrotors, commonly known as drones or unmanned aerial vehicles (UAVs), play an important role in load transportation. The complex vehicles used for transporting loads and surveillance purposes can be replaced through the ease of use and mechanical simp...
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Mino Sportelli, Orly Enrique Apolo-Apolo, Marco Fontanelli, Christian Frasconi, Michele Raffaelli, Andrea Peruzzi and Manuel Perez-Ruiz
The advancement of computer vision technology has allowed for the easy detection of weeds and other stressors in turfgrasses and agriculture. This study aimed to evaluate the feasibility of single shot object detectors for weed detection in lawns, which ...
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Arvind Panwar, Manju Khari, Sanjay Misra and Urvashi Sugandh
Despite its status as one of the most ancient sectors worldwide, agriculture continues to be a fundamental cornerstone of the global economy. Nevertheless, it faces obstacles such as a lack of trust, difficulties in tracking, and inefficiencies in managi...
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