Abstract: A vision system to recognize 3-D objects is presented. A novel notion of generalized feature makes it possible to develop a homogeneous ...

We present a vision system to recognize 3D objects. A new notion of generalized feature allows us to develop a homogeneous architecture.

Visual recognition using concurrent and layered parameter networks. Ruud Bolle; Andrea Califano; et al. 1989; CSCCVPR 1989. Evidence integration for 3D object ...

Visual recognition using concurrent and layered parameter networks. Ruud ... Evidence integration for 3D object recognition: A connectionist framework.

A framework for 3D object recognition is presented. Its flexibility and extensibility are accomplished through a uniform, parallel, and modular recognition ...

In this paper, we propose a dual network structure, termed Conformer, with the aim to couple CNN-based lo- cal features with transformer-based global ...

We are releasing DeCAF, an open-source implementation of these deep convolutional activation features, along with all associated network parameters.

May 11, 2023 · We define the i-th token as the flattened parameter vector of the i-th layer. Layers with multiple parameter groups (e.g., layers with both.

We present a residual learning framework to ease the training of networks that are substantially deeper than those used previously. We explicitly reformulate ...

Since the 3 × 3 convolutional layer possesses fewer channels, the number of parameters introduced by the corresponding SE block is also reduced. The comparison ...