Multi-Granularity Domain-Adaptive Teacher for Unsupervised Remote Sensing Object Detection by Fang Fang, Jianing Kang, Shengwen Li, Panpan Tian, Yang Liu, Chaoliang Luo, Shunping Zhou

“…MGDAT incorporates the teacher–student framework at three granularities, including pixel-, image- and instance-level feature alignment. Extensive experiments show that MGDAT surpasses SOTA baselines in detection accuracy, and exhibits great generalizability. …”
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SChanger: Change Detection From a Semantic Change and Spatial Consistency Perspective by Ziyu Zhou, Keyan Hu, Yutian Fang, Xiaoping Rui

“…We initially pretrain the model on single-temporal supervised tasks to acquire prior knowledge of instance feature extraction. The model then employs a shared-weight Siamese architecture and extended temporal fusion module to preserve this prior knowledge and is fine-tuned on change detection tasks. …”
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Leveraging advanced technologies for early detection and diagnosis of oral cancer: Warning alarm by Saantosh Saravanan, N. Aravindha Babu, Lakshmi T, Mukesh Kumar Dharmalingam Jothinathan

“…Oral cancer as a global health problem becomes more difficult to deal with, especially since developing countries are the hardest hit due to massive rates of mortality and morbidity. Detecting cancer in the early stage and providing an accurate diagnosis is important in improving the outcomes and causing less damage to the patients. …”
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SUNet: Coffee Leaf Disease Detection Using Hybrid Deep Learning Model by Deepak Thakur, Tanya Gera, Ambika Aggarwal, Madhushi Verma, Manjit Kaur, Dilbag Singh, Mohammed Amoon

“…These diseases not only reduce yield but also affect quality. Early detection and targeted treatment are crucial to mitigate their effects. …”
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Detection of Chemical Weapon Agents Using Spectroscopic Probes: A Computational Study by Letícia S. Braga, Érika F. Silva, Daiana T. Mancini, Eduardo P. da Rocha, Elaine F. F. da Cunha, Teodorico C. Ramalho

“…In this line, the fast detection of this class of compound is crucial for the determination of environmental exposure. …”
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Anterior Cruciate Ligament (ACL) Tear Detection Using Hybrid CNN Transformer by Suthir Sriram, Deependra K. Singh, D. V. Sairam, Nivethitha Vijayaraj, Thangavel Murugan

“…Classifying medical images to detect ACL (Anterior Cruciate Ligament) tears is the medical image classification task, which requires significant importance to avoid misdiagnosis. …”
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Weed detection based on deep learning from UAV imagery: A review by Lucía Sandoval-Pillajo, Iván García-Santillán, Marco Pusdá-Chulde, Adriana Giret

“…Likewise, the rapid development of deep learning architectures has driven CNN models such as ResNet for classification, YOLO for detection, U-Net for semantic segmentation, and Mask R-CNN for weed instance segmentation, with a tendency towards new Transformer-based and hybrid architectures. …”
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Infectious Hypodermal and Hematopoietic Necrosis Virus Detection in Shrimp Farming Pond Sediments by Ruoxuan LÜ, Xiuhua WANG, Meifeng WANG, Xinyu LIAN, Chen LI, Hua XU, Weili YIN, Peng JIA, Bing YANG

“…For instance, for a method has been developed for detecting Cyprinid herpesvirus 3 (CyHV-3) in environmental waters using virus concentration methods and TaqMan polymerase chain reaction (PCR). …”
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FBD-SV-2024: Flying Bird Object Detection Dataset in Surveillance Video by Zi-Wei Sun, Ze-Xi Hua, Heng-Chao Li, Zhi-Peng Qi, Xiang Li, Yan Li, Jin-Chi Zhang

“…Among them, 23,833 frames contain 28,366 instances of flying birds. The proposed dataset of flying birds in surveillance videos is collected from realistic surveillance scenarios, where the birds exhibit characteristics such as inconspicuous features in single frames (in some instances), generally small sizes, and shape variability during flight. …”
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Edge Convolutional Networks for Style Change Detection in Arabic Multi-Authored Text by Abeer Saad Alsheddi, Mohamed El Bachir Menai

“…The style change detection (SCD) task asks to find the positions of authors’ style changes within multi-authored texts. …”
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Rotifer detection and tracking framework using deep learning for automatic culture systems by Naoto Ienaga, Toshinori Takashi, Hitoko Tamamizu, Kei Terayama

“…We propose a deep learning framework for detecting and tracking rotifers as a basis for such automation and carefully verify its accuracy. …”
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Hardware Trojan Detection in Open-Source Hardware Designs Using Machine Learning by Victor Takashi Hayashi, Wilson Vicente Ruggiero

“…The globalization of the hardware supply chain reduces costs but increases security challenges with the potential insertion of hardware trojans by third parties. Traditional detection methods face scalability limitations by relying solely on simple examples (e.g., AES). …”
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An optimized stacking-based TinyML model for attack detection in IoT networks. by Anshika Sharma, Shalli Rani, Mohammad Shabaz

“…To address these challenges, a stacking-based Tiny Machine Learning (TinyML) models has been proposed for attack detection in IoT networks. This ensures detection efficiently and without additional computational overhead. …”
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Design and Analysis of an Effective Architecture for Machine Learning Based Intrusion Detection Systems by Noora Alromaihi, Mohsen Rouached, Aymen Akremi

“…This behavior is often perceived by IDSs as infrequent attacks, thus diminishing the effectiveness of detection. In this context, this paper aims to create a machine learning-based IDS model able to detect malicious traffic received by different organizational network interfaces. …”
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Origins of Very Low Helium Abundance Streams Detected in the Solar Wind Plasma by Yogesh, N. Gopalswamy, D. Chakrabarty, Parisa Mostafavi, Seiji Yashiro, Nandita Srivastava, Leon Ofman

“…These low- A _He occurrences are detected both near the Sun and at 1 au. The low- A _He events are generally observed near the heliospheric current sheet. …”
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Detection of Weak Radar Return Signals Based on Pseudo-Time Domain Algorithm by Kaili Wang, Kai Yuan, Bo Bai, Rongxin Tang

“…In cases where the SNR reaches −40 dB, the detection success rate exceeds 95% in most instances. …”
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A texture enhanced attention model for defect detection in thermal protection materials by Jialin Song, Zhaoba Wang, Kailiang Xue, Youxing Chen, Guodong Guo, Maozhen Li, Asoke K. Nandi

“…To address these issues, we first construct a thermal protection material digital radiographic (DR) image dataset (TPMDR-dataset), which contains 670 images from actual production and 6,269 defect instances annotated under expert guidance. And we propose an innovative texture-enhanced attention defect detection (TADD) model that enables accurate, efficient, and real-time defect detection. …”
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Multilingual hope speech detection from tweets using transfer learning models by Muhammad Ahmad, Iqra Ameer, Wareesa Sharif, Sardar Usman, Muhammad Muzamil, Ameer Hamza, Muhammad Jalal, Ildar Batyrshin, Grigori Sidorov

“…In recent years, researchers have focused on the automatic detection of hope speech in languages such as Russian, English, Hindi, Spanish, and Bengali. …”
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An Adaptive Intrusion Detection System for Evolving IoT Threats: An Autoencoder-FNN Fusion by J. Jasmine Shirley, M. Priya

“…The increasing sophistication of attacks targeting the Internet of Things environment underscores the critical need for robust intrusion detection systems. This study introduces a specialized IDS classification approach to address IoT networks’ evolving and diverse threat landscape. …”
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Integrating Explanations into CNNs by Adopting Spiking Attention Block for Skin Cancer Detection by Inzamam Mashood Nasir, Sara Tehsin, Robertas Damaševičius, Rytis Maskeliūnas

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