OBJECT TRACKING – MLT SOLUTION FOR METI / NEDO EDGE AI COMPETITION

The MLT team Yoovraj Shinde, Alisher Abdulkhaev, Naveen Kumar, Hajime Kato and Benjamin Ioller developed an object detection and object tracking system and scored a gold medal and 3rd prize in the competition. Code and documentation were open sourced and are available on our MLT GitHub.

CNN ARCHITECTURES: DENSENET

This is part of the CNN Architectures series by Dimitris Katsios. Find all CNN Architectures online: Notebooks: MLT GitHubVideo tutorials: YouTubeSupport MLT on Patreon DenseNet We will use the tensorflow.keras Functional API to build DenseNet from the original paper: “Densely Connected Convolutional Networks” by Gao Huang, Zhuang Liu, Laurens van der Maaten, Kilian Q. Weinberger. In the paper we can read: [i] “Note that … Continue reading CNN ARCHITECTURES: DENSENET

CNN ARCHITECTURES: SQUEEZENET

This is part of the CNN Architectures series by Dimitris Katsios. Find all CNN Architectures online: Notebooks: MLT GitHubVideo tutorials: YouTubeSupport MLT on Patreon SqueezeNet We will use the tensorflow.keras Functional API to build SqueezeNet from the original paper: “SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size” by Forrest N. Iandola, Song Han, Matthew W. Moskewicz, Khalid Ashraf, … Continue reading CNN ARCHITECTURES: SQUEEZENET