Ultra-lightweight tomatoes disease recognition method based on efficient attention mechanism in complex environment by Wenbin Sun, Zhilong Xu, Kang Xu, Lin Ru, Ranbing Yang, Rong Wang, Jiejie Xing

“…To address these issues, this study proposes a framework that integrates tomato leaf detection with leaf disease recognition. This framework includes a leaf detection model designed for diverse and complex environments, along with an ultra-lightweight model for recognizing tomato leaf diseases. …”
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MEViT: Generalization of Deepfake Detection With Meta-Learning EfficientNet Vision Transformer by Van-Nhan Tran, Hoanh-Su Le, Piljoo Choi, Suk-Hwan Lee, Ki-Ryong Kwon

“…In this study, we propose a model called MEViT, which integrates the EfficientNet Vision Transformer with a meta-learning framework to enhance generalization in deepfake detection. …”
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OE-YOLO: An EfficientNet-Based YOLO Network for Rice Panicle Detection by Hongqing Wu, Maoxue Guan, Jiannan Chen, Yue Pan, Jiayu Zheng, Zichen Jin, Hai Li, Suiyan Tan

“…Accurately detecting rice panicles in complex field environments remains challenging due to their small size, dense distribution, diverse growth directions, and easy confusion with the background. …”
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Benthos-DETR: a high-precision efficient network for benthic organisms detection by Weibo Rao, Gang Chen, Yifei Zhang, Jue Cang, Shusen Chen, Chenyang Wang

“…This study proposes Benthos-DETR, a benthic organisms detection network based on the RT-DETR network. In the backbone of Benthos-DETR network, the Efficient Block with the C2f module reinforces the shallow feature extraction operation in Benthos-DETR, enhancing the algorithm’s multi-scale perception. …”
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BrYOLO-Mamba: A Approach to Efficient Tracheal Lesion Detection in Bronchoscopy by Yuejiao Cao, Jianzhong Zhang, Ruibing Zhuo, Jin Zhao, Yanting Dong, Tanzhen Liu, Hui Zhao

“…Although artificial intelligence has made significant progress in enhancing the accuracy and efficiency of medical image diagnosis, current systems still struggle to effectively capture long-range dependencies and fine-grained features in complex medical images. …”
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Ensemble deep learning and anomaly detection framework for automatic audio classification: Insights into deer vocalizations by Salem Ibrahim Salem, Sakae Shirayama, Sho Shimazaki, Kazuo Oki

“…This segmentation method relies on acoustic anomaly detection and can markedly improve computational efficiency, facilitating deployment in environments with limited resources. …”
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MDPruner: Meta-Learning Driven Dynamic Filter Pruning for Efficient Object Detection by Lingyun Zhou, Xiaoyong Liu

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Utilizing Detectron2 for accurate and efficient colon cancer detection in histopathological images by Luxi Chen, Jie Shen, Xinyu Li, Rongzhou Li, Xiaoyun Gao, Xiaoyun Gao, Xinyue Chen, Xinyue Chen, Xiaotian Pan, Xiaotian Pan, Xiaosheng Jin

“…The framework demonstrated high computational efficiency and robustness in handling the complexity of medical image data.DiscussionThese results highlight Detectron2’s effectiveness as a powerful tool for computer-aided diagnostics in colon cancer detection. …”
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DRBD-YOLOv8: A Lightweight and Efficient Anti-UAV Detection Model by Panpan Jiang, Xiaohua Yang, Yaping Wan, Tiejun Zeng, Mingxing Nie, Zhenghai Liu

“…To address these limitations, a lightweight and efficient anti-UAV detection model, DRBD-YOLOv8, is proposed in this paper. …”
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Low complexity hybrid iterative algorithm based signal detection in massive MIMO system by Shufeng ZHAO, Bin SHEN, Furong YANG

“…Among the uplink signal detection algorithms for massive MIMO systems,the minimum mean square error (MMSE) algorithm can achieve the near-optimal linear detection performance.However,conventional MMSE usually involves high complexity due to the required matrix inversion of large-size matrix,which makes it hard to implement in realistic applications.Based on joint steepest descent (SD) algorithm and Gauss-Seidel iteration,a low complexity hybrid iterative detection algorithm was proposed.The SD algorithm was employed to obtain an efficient searching direction for the following Gauss-Seidel to speed up convergence.Meanwhile,an approximated method was also proposed to compute the bit log-likelihood ratio (LLR) for soft channel decoding.Simulation results verify that the proposed algorithm can converge rapidly and achieve its performance quite close to that of the MMSE algorithm with only a small number of iterations.Meanwhile,the complexity is reduced by an order of magnitude,which is kept consistently of O(K ²).…”
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On the Design of Near-Optimal Generalized Block-Based Spatial Modulation With Low Detection Complexity by Yen-Ming Chen, Wei-Lun Lin, Heng Lee, Tsung-Lin Chen

“…However, independently designing the constellation cardinality and TACs leads to limited performance gains and an exponential increase in complexity, particularly under maximum-likelihood (ML) detection. …”
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Nearest neighbor permutation entropy detects phase transitions in complex high-pressure systems by Arthur A. B. Pessa, Leonardo G. J. M. Voltarelli, Lúcio Cardozo-Filho, Andres G. M. Tamara, Claudio Dariva, Papa M. Ndiaye, Matjaž Perc, Haroldo V. Ribeiro

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A Precise Detection Method for Tomato Fruit Ripeness and Picking Points in Complex Environments by Xinfa Wang, Xuan Wen, Yi Li, Chenfan Du, Duokuo Zhang, Chengxiu Sun, Bihua Chen

“…Aiming at the problems faced in practical applications, such as low accuracy of tomato ripeness and picking points detection in complex greenhouse environments, which leads to wrong picking, missed picking, and fruit damage by robots, this study proposes the YOLO-TMPPD (Tomato Maturity and Picking Point Detection) model. …”
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REDETR-RISTD: Real-Time Long-Range Infrared Small Target Detection Network Based on the Reparameterized Efficient Detection Transformer by Ning Li, Daozhi Wei

“…This happens because the targets are small in size, have a weak signal-to-noise ratio (SNR), and are surrounded by complex backgrounds. A novel real-time long-range infrared small target detection network based on the Reparameterized Efficient Detection Transformer (REDETR-RISTD) is proposed. …”
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ASD-YOLO: a lightweight network for coffee fruit ripening detection in complex scenarios by Baofeng Ye, Baofeng Ye, Renzheng Xue, Renzheng Xue, Haiqiang Xu, Haiqiang Xu

“…In order to improve the detection efficiency of coffee fruit maturity, this paper proposes an improved detection method based on YOLOV7 to efficiently identify the maturity of coffee fruits, called ASD-YOLO. …”
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YOLOv8n-CSD: A Lightweight Detection Method for Nectarines in Complex Environments by Guohai Zhang, Xiaohui Yang, Danyang Lv, Yuqian Zhao, Peng Liu

“…To improve the accuracy of nectarine fruit recognition in complex environments and to increase the efficiency of automatic orchard-picking robots, a lightweight nectarine detection method, YOLOv8n-CSD, is proposed in this study. …”
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SDES-YOLO: A high-precision and lightweight model for fall detection in complex environments by Xiangqian Huang, Xiaoming Li, Limengzi Yuan, Zhao Jiang, Hongwei Jin, Wanghao Wu, Ru Cai, Meilian Zheng, Hongpeng Bai

“…In the field of object detection, while YOLOv8 has recently made notable strides in detection accuracy and speed, it still faces challenges in detecting falls due to variations in lighting, occlusions, and complex human postures. …”
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Adaptive Fault Detection for Complex Dynamic Processes Based on JIT Updated Data Set by Jinna Li, Yuan Li, Haibin Yu, Yanhong Xie, Cheng Zhang

“…A novel fault detection technique is proposed to explicitly account for the nonlinear, dynamic, and multimodal problems existed in the practical and complex dynamic processes. …”
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Specific and Rapid Detection of Mycobacterium tuberculosis Complex in Clinical Samples by Polymerase Chain Reaction by Anamika Singh, Vijendra Kumar Kashyap

“…This method, by well distinguishing between MTB complex and NTM, presented a fast and accurate method to detect and diagnose mycobacterial infections more efficiently and could thereby help in better patient management particularly considering the increase in mycobacterial infections due to emergence of NTM over the past decades.…”
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A Parts Detection Network for Switch Machine Parts in Complex Rail Transit Scenarios by Jiu Yong, Jianwu Dang, Wenxuan Deng

“…This article proposes a complex scene rail transit switch machine parts detection network YOLO-SMPDNet (YOLO-based Switch Machine Parts Detecting Network). …”
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