yolo deep learning

The 2016 is a very important historical node, signifying that the AI system of unity of knowledge and line will go to the historical stage. It changes not only the next go, it will change a lot of things. --KaiyuOn the "Adas and autonomous Driving Trends forum" of the "2016 Smart cars and Shanghai Forum", Dr. Kaiyu, founder and CEO of Horizon Robotics, delivered a keynote speech entitled "The road to autonomous driving based on deep

The theme report of "Transfer model of deep learning" shorthand and commentary (iv) Bai Chu of the Red bean Family concern 2017.11.04 22:33* 3275 reading 141 comments 0 like 0 The author presses: machine learning is moving towards a new era of interpretive models based on "semantics". Migration learning is likely to ta

The author Matthew May is a computer postgraduate in parallel machine learning algorithms, and Matthew is also a data mining learner, a data enthusiast, and a dedicated machine-learning scientist. Open source tools play an increasingly important role in data science workflows. GitHub Ten deep learning projects, which i

implementation in Toolbox is very simple:In the NNTRAIN.M:batch_x = batch_x.* (rand (Size (batch_x)) >nn.inputzeromaskedfraction)That is, the size of the (nn.inputzeromaskedfraction) part of the X-0,denoising Autoencoder appears to be stronger than sparse autoencoderContractive auto-encoders:This variant is "Contractive auto-encoders:explicit invariance during feature extraction" proposedThis paper also summarizes a bit of autoencoder, it feels goodThe contractive autoencoders model is:whichThe

Structured Query language to manipulate database.for example:1. INSERT into Events VALUES ("rubyconf", 100); Insert a piece of data into the events table2. SELECT * from events; Take out all the dataTri ACID (4 properties)Transaction: A process of doing business. Package a set of actions to execute together.Use begin;...commit; it can guarantee the correctness of data access, either succeed together or fail together.Atomicity: A transaction is an atom.Consistency: Consistency ensures that the i

-ser Ies-based Anomaly DetectIon algorithms AI Class Introduction search algorithms A-star heuristic search Constraint satisfaction algorithms with AP Plications in computer Vision and scheduling Robot Motion planning hillclimbing, simulated annealing and genetic algorithm S 2. Stanford University opened a course on "deep learning and natural language processing" in March: Cs224d:deep

In recent years, machine learning, represented by deep learning, has become more and more in the field of health care. According to the type of data processed can be divided into numerical, textual and image data; This paper focuses on text data. Clinical Diagnostic Decisions: (Miotto r,et al;2016) [1] A new unsupervised depth feature

variables, and the parent process has also seen this modification. The vfork function may occur because the fork of the early system did not implement the write-time replication technology, resulting in a lot of useless work in each fork call (in most cases, it is called exec to execute a new program after fork) the efficiency is not high, so the vfork function is created. The current implementation basically uses the write-time replication technology, and when the vfork function is used improp

1. Why add pooling (pooling) to the convolutional networkIf you only use convolutional operations to reduce the size of the feature map, you will lose a lot of information. So think of a way to reduce the volume of stride, leaving most of the information, through pooling to reduce the size of feature map.Advantages of pooling:1. Pooled operation does not increase parameters2. Experimental results show that the model with pooling is more accurateDisadvantages of pooling:1. Because the stride of t