Improvement of ablation experiment results for YOLOv7 modules.

Improvement of ablation experiment results for YOLOv7 modules.

<p>(a) The original YOLO model (b)YOLOv7+SimAM. (c)YOLOv7+SimAM+Pconv.</p>

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Guoqing Zhang (151441) (author)
مؤلفون آخرون: Jiandong Liu (6064643) (author), Yongxiang Zhao (671364) (author), Wei Luo (80175) (author), Keyu Mei (20542959) (author), Penggang Wang (6038210) (author), Yubin Song (3205194) (author), Xiaoliang Li (720274) (author)
منشور في: 2025
الموضوعات:
Science Policy
Space Science
Biological Sciences not elsewhere classified
Information Systems not elsewhere classified
unmanned aerial vehicles
uavs ), utilizing
transfer learning techniques
suppressing irrelevant information
reducing missed detections
partially occluded targets
offering valuable insights
global economy expands
deep sort algorithms
deep sort algorithm
become increasingly crucial
ship monitoring scenarios
model &# 8217
limited ship data
deep sort model
emphasizing salient features
enhanced system achieves
demonstrated robust performance
improves detection accuracy
ship detection
model training
stable features
xlink ">
waterway transportation
unlinked tracks
significant challenges
partial convolution
logistics sector
irregularly shaped
iou metric
invalid regions
growth presents
feature extraction
false negatives
extensive evaluation
diou metric
detected objects
critical reference
computational demands
artificial intelligence
article introduces
also reduces
address issues
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