MASSACHUSETTS INSTITUTE OF TECHNOLOGY A Trainable System for Object Detection in Images and Video SequencesPapageorgiou, Constantine P
YOLO (You Only Look Once) has become a central object detection model that mostly works in real-time environments with impressive accuracy and speed. In recent years, object detection has been a prominent task in CV (Computer Vision) [1] for reliable location and identification of objects withi...
Rui Qian, Xin Lai, Xirong Li: 3D Object Detection for Autonomous Driving: A Survey (Pattern Recognition 2022: IF=8.518) - rui-qian/SoTA-3D-Object-Detection
Object Detection With Deep Learning: A ReviewDue to object detection s close relationship with video analysis and image understanding, it has attracted much research attention in recent years.Traditional object detection methods are built on handcrafted features and shallow trainable architectures.Their pe...
This structure helps to reduce the trainable parameters in the block. The compression layer, also known as the bottleneck layer, decreases the number of channels with a 1 × 1 convolutional layer. Each layer has a batch normalization (BN) layer and Swish function except the projection layer. ...
Step 3: Customize Model for Task for layer in base_model.layers: layer.trainable = Falsex = GlobalAveragePooling2D()(base_model.output)output = Dense(num_classes, activation='softmax')(x)model = Model(inputs=base_model.input, outputs=output) Step 4: Compile Model model.compile(optimizer=...
{t}\)and an object buffer of the codes in the preceding frames\({z}_{1:K}^{1:t-1}\). The dynamics module comprises two trainable components: a ‘slotted’ object-based LSTM and an interaction network (IN). Predictions are made by computing interactions from each slot in the LSTM’...
By learning many detection algorithms and does not compromise an object class in terms of a subset of an overcomplete the ability of the system to detect non-moving objects. dictionary of wavelet basisfunctions, we derive a com- Initial work on the detection of rigid objects in pact ...
In order to reduce the occurrence of highway incidents, an object detection algorithm for highway intrusion was proposed in this paper. Firstly, a new feature extraction module was proposed to better preserve the main information. Secondly, a new feature fusion method was proposed to improve the...
Trainable bag of freebies The YOLOv7 authors used gradient flow propagation paths to analyze how re-parameterized convolution should be combined with different networks. The above diagram shows how the convolutional blocks should be placed, with the check-marked options representing that they worked....