Evolution of AI enabled healthcare systems using textual data with a pretrained BERT deep learning model by Yi Jie Wang, Wei Chong Choo, Keng Yap Ng, Ran Bi, Peng Wei Wang

“…The findings point out the market trends of the Internet of Things, data security and image processing. This study not only reveals current research hotspots and technological trends in AI for healthcare but also proposes an advanced research method. …”
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A Novel Dataset for Polyp Segmentation and Detection Using a Vision-Language Model by Mahdiyeh Alilou, Javad Mozaffari, Abdollah Amirkhani, Shahriar B. Shokouhi, Alireza Khafaf

“…Colonoscopy is one of the most effective methods for the detection of polyps, and deep learning algorithms can be utilized for colonoscopy image processing. …”
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High precision water quality retrieval in Dianchi Lake using Gaofen 5 data and machine learning methods by Yuewen Feng, Jun Zhang, Sanjie Guo, Yunbai Zhang, Zhongwei Zhang

“…In this paper, the Advanced Hyperspectral Imager (AHSI) data from the GF-5 satellite was used to analyze the Dianchi Lake. …”
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FA-Unet: A Deep Learning Method with Fusion of Frequency Domain Features for Fruit Leaf Disease Identification by Xiaowei Li, Wenlin Wu, Fenghua Zhu, Shenhao Guan, Wenliang Zhang, Zheng Li

“…In the recognition of fruit leaf diseases, image recognition technology based on deep learning has received increasing attention. …”
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Development and testing of an open source mobile application for audiometry test result analysis and diagnosis support by Michał Kassjański, Marcin Kulawiak, Tomasz Przewoźny, Dmitry Tretiakow, Andrzej Molisz

“…For this purpose, the application implements several artificial intelligence and image processing techniques, including YOLOv5, Optical Character Recognition (OCR) and Hough Transform. …”
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Real-Time Transformer Detection of Underwater Objects Based on Lightweight Gated Convolutional Network by Yuhui LI, Huixia CUI, Yaomin LI, Senping JIA

“…To address the challenges in underwater object detection algorithms, including difficult image feature processing, redundant model architectures, and excessive parameter numbers, this paper proposed a real-time Transformer detection method for underwater objects based on a lightweight gated convolutional network. …”
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Artificial Intelligence Driven Human Identification by Purushottam Sharma, Aazar Imran Khan, Samyak Jain, Abhishek Srivastava

“…This is achieved by incorporating computer vision, digital image processing, vectorization, artificial intelligence, and multi-threading. …”
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Intelligent Recognition and Automated Production of Chili Peppers: A Review Addressing Varietal Diversity and Technological Requirements by Sheng Tai, Zhong Tang, Bin Li, Shiguo Wang, Xiaohu Guo

“…For perception and recognition, the review covers the evolution from traditional image processing to deep learning-based methods (e.g., YOLO and Mask R-CNN achieving a mAP > 90% in specific studies) for pepper detection, segmentation, and fine-grained cultivar identification, analyzing the performance and optimization in complex environments. …”
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Development of Biological Movement Recognition by Interaction between Active Basis Model and Fuzzy Optical Flow Division by Bardia Yousefi, Chu Kiong Loo

“…Following the study on computational neuroscience through functional magnetic resonance imaging claimed that human action recognition in the brain of mammalian pursues two separated streams, that is, dorsal and ventral streams. …”
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Enhancing burned area monitoring with VIIRS dataset: A case study in Sub-Saharan Africa by Boris Ouattara, Michael Thiel, Barbara Sponholz, Heiko Paeth, Marta Yebra, Florent Mouillot, Patrick Kacic, Kwame Hackman

“…The algorithm encompasses several steps, including pre-processing individual scenes, creating cloud-free composites, generating binary reference data for burned and non-burned areas, conducting a supervised classification using random forest, and performing region shaping. …”
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A Study of Mixed Non-Motorized Traffic Flow Characteristics and Capacity Based on Multi-Source Video Data by Guobin Gu, Xin Sun, Benxiao Lou, Xiang Wang, Bingheng Yang, Jianqiu Chen, Dan Zhou, Shiqian Huang, Qingwei Hu, Chun Bao

“…The video data were processed with an image detection algorithm based on the YOLO convolutional neural network and a video tracking algorithm using the DeepSORT multi-target tracking model, extracting data on traffic flow, density, speed, and rider characteristics. …”
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Reconstruction for Scanning LiDAR with Array GM-APD on Mobile Platform by Di Liu, Jianfeng Sun, Wei Lu, Sining Li, Xin Zhou

“…Array Geiger-mode avalanche photodiode (GM-APD) Light Detection and Ranging (LiDAR) has the advantages of high sensitivity and long imaging range. However, due to its operating principle, GM-APD LiDAR requires processing based on multiple-laser-pulse data to complete the target reconstruction. …”
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R-SABMNet: A YOLOv8-Based Model for Oriented SAR Ship Detection with Spatial Adaptive Aggregation by Xiaoting Li, Wei Duan, Xikai Fu, Xiaolei Lv

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Developmental experience of the geoinformation system for floodplain lands of the Don basin by D. A. Solodovnikov, S. S. Shinkarenko, N. M. Khavanskaya, N. A. Kukushkina

“…The area of the river basin (tributary), the slope and exposure of the sides of the valley, the slope of the river bed and the length of the watercourse, the area of floodplains, agricultural land on floodplain lands, forest land, the tortuosity of the river and the development of the floodplain and the number, area and volume of small reservoirs were obtained by processing digital terrain models employing functions of the Spatial Analyst module and satellite images in automatic mode.Results. …”
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InCrowd-VI: A Realistic Visual–Inertial Dataset for Evaluating Simultaneous Localization and Mapping in Indoor Pedestrian-Rich Spaces for Human Navigation by Marziyeh Bamdad, Hans-Peter Hutter, Alireza Darvishy

“…InCrowd-VI features 58 sequences totaling a 5 km trajectory length and 1.5 h of recording time, including RGB, stereo images, and IMU measurements. The dataset captures important challenges such as pedestrian occlusions, varying crowd densities, complex layouts, and lighting changes. …”
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Scalable Hyperspectral Enhancement via Patch-Wise Sparse Residual Learning: Insights from Super-Resolved EnMAP Data by Parth Naik, Rupsa Chakraborty, Sam Thiele, Richard Gloaguen

“…A majority of hyperspectral super-resolution methods aim to enhance the spatial resolution of hyperspectral imaging data (HSI) by integrating high-resolution multispectral imaging data (MSI), leveraging rich spectral information for various geospatial applications. …”
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Single LED Beacon-Based 3-D Indoor Positioning Using Off-the-Shelf Devices by Yinan Hou, Shilin Xiao, Meihua Bi, Yuankai Xue, Wansheng Pan, Weisheng Hu

“…In this paper, we demonstrate a single light-emitting diode (LED) beacon-based 3-D indoor positioning scheme by experiment and theoretical derivation, which can overcome the limitation of multiple LED beacons involved in one positioning process. Only off-the-shelf devices are employed in this scheme, such as an image sensor, a gyroscope, and a photodiode, which have been integrated in most of commercial available smartphones so that it is compatible with most of mobile terminals. …”
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Ripening Study Based on Multi-Structural Inversion of Cherry Tomato qMRI by Yanan Li, Jingfa Yao, Wenhui Yang, Zhao Wei, Peng Luan, Guifa Teng

“…The structural T2 relaxation inversion was refined by integrating an ACS-CIPSO algorithm. This approach addresses the challenge of low signal-to-noise ratios in multi-echo MRI images from low-field equipment by introducing an innovative solution that effectively reduces voxel noise while retaining structural relaxation variability. …”
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Blind super-resolution network based on local fuzzy discriminative loss for fabric data augmentation by Ning Dai, Xiaohan Hu, Kaixin Xu, Xudong Hu, Yanhong Yuan, Bo Cao, Luhong Shi

“…To address these challenges, this paper proposes a blind super-resolution algorithm for fabric defect data augmentation. The model is based on Real-ESRGAN and has been optimized specifically for the resolution degradation module to better adapt to the resolution degradation process in fabric images. …”
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Automated ejection fraction and risk stratification in cardiomyopathy patients with diverse LV geometry using 2D echocardiography by Ziwei Zhu, Ke Fan, Shuyuan Zhang, Tingting Hu, Jingyi Li, Ze Zhao, Ye Jin, Shuyang Zhang

“…For all patients with cardiomyopathy, we computed LV volume on apical two- and four-chamber views processed with novel DeepLabV3+ algorithm and calculate EF using Simpson’s method. …”
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