… Figure 6: Retrieval results on a dataset of 80 million images using the original gist descriptor,
and hash codes build with spectral hashing with 32 bits and 64 bits. The input image …

… in methods based on “semantic hashing”, ie compact binary … to solve exactly, but a spectral
relaxation gives an algorithm … similar to the recently proposed Spectral Hashing (SH) method. …

… spectral hashing with semantically consistent graph approach in this paper. It improves spectral
hashing, a state-of-the-art hashing … of images in the hash function learning process. The …

… the unsupervised spectral hashing due to its effective manifold embedding. Existing spectral
hashing methods mainly suffer from two problems, ie, the inefficient spectral candidate and …

… In this paper, we study spectral hashing (SH), which is a classical method of unsupervised
hashing. In general, SH solves … 1) Spectral Hashing: We are particularly interested in spectral …

A better similarity index structure for high-dimensional feature datapoints is very desirable
for building scalable content-based search systems on feature-rich dataset. In this paper, we …

… novel unsupervised discrete hashing approach, namely robust discrete spectral hashing (RDSH),
which targets at jointly learning discrete binary codes as well as robust hash functions. …

… The crucial problem is to generalize spectral hashing for new data points. That could be
solved by … In this section we connect spectral hashing with spectral clustering and use the …

… • In the first stage of the two-step hashing, we propose a novel algorithm which is based
on spectral embedding to simultaneously learn single modality representations and a cross-…

… However, the spectral solution in real value of such methods … a so-called spectral rotation
technique to the spectral hashing … -the-art hashing methods, especially the spectral graph ones. …