Pseudo-code of MACOA. by Xingtao Wu (22139242)

ROI Thresholding Methods in Endogenous fluorophore images. by Araven Tiroumalechetty (17827252)

ROI Restriction and Visualization in WormSNAP GUI. by Araven Tiroumalechetty (17827252)

ASTCT_data & code by Ju Peng (13922445)

“…<pre>This repository contains the code and datasets of the ATSTC algorithm proposed in the study for trajectory clustering which has been accepted by IJGIS. …”

The code for sample size calculation. by Ying Zhou (25031)

The principle of Partial Convolution. by Junjie Lu (160350)

“…To address this issue, this paper proposes FCMI-YOLO, a real-time fire detection algorithm optimized for edge devices. Firstly, the FasterNext module is proposed to reduce computational cost and enhance detection precision through lightweight design. …”

Ablation experiments results of YOLOv5s. by Junjie Lu (160350)

“…To address this issue, this paper proposes FCMI-YOLO, a real-time fire detection algorithm optimized for edge devices. Firstly, the FasterNext module is proposed to reduce computational cost and enhance detection precision through lightweight design. …”

Overall network architecture of FCMI-YOLO. by Junjie Lu (160350)

“…To address this issue, this paper proposes FCMI-YOLO, a real-time fire detection algorithm optimized for edge devices. Firstly, the FasterNext module is proposed to reduce computational cost and enhance detection precision through lightweight design. …”

The principle of MLCA mechanism. by Junjie Lu (160350)

“…To address this issue, this paper proposes FCMI-YOLO, a real-time fire detection algorithm optimized for edge devices. Firstly, the FasterNext module is proposed to reduce computational cost and enhance detection precision through lightweight design. …”

Parameters of the dataset. by Junjie Lu (160350)

“…To address this issue, this paper proposes FCMI-YOLO, a real-time fire detection algorithm optimized for edge devices. Firstly, the FasterNext module is proposed to reduce computational cost and enhance detection precision through lightweight design. …”

Comparison of mAP@0.5 for different ratios. by Junjie Lu (160350)

“…To address this issue, this paper proposes FCMI-YOLO, a real-time fire detection algorithm optimized for edge devices. Firstly, the FasterNext module is proposed to reduce computational cost and enhance detection precision through lightweight design. …”

Primary training parameters for the model. by Junjie Lu (160350)

“…To address this issue, this paper proposes FCMI-YOLO, a real-time fire detection algorithm optimized for edge devices. Firstly, the FasterNext module is proposed to reduce computational cost and enhance detection precision through lightweight design. …”

Distribution of the dataset. by Junjie Lu (160350)

“…To address this issue, this paper proposes FCMI-YOLO, a real-time fire detection algorithm optimized for edge devices. Firstly, the FasterNext module is proposed to reduce computational cost and enhance detection precision through lightweight design. …”

Parameters of the FasterNext and C3. by Junjie Lu (160350)

“…To address this issue, this paper proposes FCMI-YOLO, a real-time fire detection algorithm optimized for edge devices. Firstly, the FasterNext module is proposed to reduce computational cost and enhance detection precision through lightweight design. …”

System diagram. by Junjie Lu (160350)

“…To address this issue, this paper proposes FCMI-YOLO, a real-time fire detection algorithm optimized for edge devices. Firstly, the FasterNext module is proposed to reduce computational cost and enhance detection precision through lightweight design. …”

Schematic diagram of Inner-IoU. by Junjie Lu (160350)

“…To address this issue, this paper proposes FCMI-YOLO, a real-time fire detection algorithm optimized for edge devices. Firstly, the FasterNext module is proposed to reduce computational cost and enhance detection precision through lightweight design. …”

Model train environment. by Junjie Lu (160350)

“…To address this issue, this paper proposes FCMI-YOLO, a real-time fire detection algorithm optimized for edge devices. Firstly, the FasterNext module is proposed to reduce computational cost and enhance detection precision through lightweight design. …”

The structure of FasterNext. by Junjie Lu (160350)

“…To address this issue, this paper proposes FCMI-YOLO, a real-time fire detection algorithm optimized for edge devices. Firstly, the FasterNext module is proposed to reduce computational cost and enhance detection precision through lightweight design. …”

The structure of MLCA mechanism. by Junjie Lu (160350)

“…To address this issue, this paper proposes FCMI-YOLO, a real-time fire detection algorithm optimized for edge devices. Firstly, the FasterNext module is proposed to reduce computational cost and enhance detection precision through lightweight design. …”

MAT-PointPillars network structure diagram. by Xinpeng Yao (18882573)