In this paper, we provide the observation that too few queries assigned as positive samples
in DETR with one-to-one set matching leads to sparse supervision on the encoder's output …

Transformer-based detectors (DETRs) are becoming popular for their simple framework, but
the large model size and heavy time consumption hinder their deployment in the real world …

The 3-D object detector usually uses a framework similar to 2-D detection and benefits from
the advancements of 2-D detection tasks. In these frameworks, it is necessary to make the …

Underwater target detection is a critical task in various applications, including environmental
monitoring, underwater exploration, and marine resource management. As the demand for …

Unmanned surface vehicles (USVs) are distinguished by their intelligence, compactness,
and absence of human casualties, making them a vital component of the maritime industry …

The Detection Transformer (DETR) has revolutionized the design of CNN-based object
detection systems, showcasing impressive performance. However, its potential in the …

Feature pyramid representations have been widely adopted in the object detection literature
for better handling of variations in scale, which provide abundant information from various …

Most of the existing object detection methods have complicated hand-designed
components, such as nonmaximum suppression procedures and manual resizing of anchor …

In recent years, deep learning has made remarkable breakthroughs in single-image super-
resolution (SISR). However, the improvements often come with the increased network size …

X‐ray security checks aim to detect contraband in luggage; however, the detection accuracy
is hindered by the overlapping and significant size differences of objects in X‐ray images. To …