Qilin Zhang

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We examine an under-explored visual recognition problem, where we have a main view along with an auxiliary view of visual information present in the training data, but merely the main view is available in the test data. To effectively leverage the auxiliary view to train a stronger classifier, we propose a collaborative auxiliary learning framework based on(More)
This paper presents a series of user parameter-free iterative Sparse Asymptotic Minimum Variance (SAMV) approaches for array processing applications based on the asymptotically minimum variance (AMV) criterion. With the assumption of abundant snapshots in the direction-of-arrival (DOA) estimation problem, the signal powers and noise variance are jointly(More)
  • Dongshuai Li, Mohammad Azadifar, +5 authors Zhenhui Wang
  • 2016
—In this paper, we present a theoretical analysis of the propagation effects of lightning electromagnetic fields over a mountainous terrain. The analysis is supported by experimental observations consisting of simultaneous records of lightning currents and electric fields associated with upward negative lightning flashes to the instrumented Säntis tower in(More)
TO THE EDITOR Psoriasis is a common, chronic, inflam-matory, organ-specific autoimmune skin disease with a complex genetic background (Nestle et al., 2009; Zhang et al., 2013). Psoriasis vulgaris (PsV) is the most common type, accounting for approximately 85–90% of all psoriasis patients, and characterized by raised, well-demarcated, erythematous oval(More)
Particle Swarm Optimization (PSO) is a new paradigm of Swarm Intelligence which proposes that the co-operation of individuals promotes the evolution of the swarm. Recently, a modified Particle Swarm Optimizer (MLPSO) has been succeeded in solving truss topological optimization problems with continuous design variable and competitive results were obtained.(More)
as a comparatively new developed stochastic method particle swarm optimization (PSO), it is widely applied to various kinds of optimization problems especially of nonlinear, non-differentiable or non-convex types. In this paper, a modified guaranteed converged particle swarm algorithm (MGCPSO) is proposed in this paper, which is inspired by guaranteed(More)
INTRODUCTION It is a common view that consistency and blood supply of pituitary adenoma (PA) can influence the surgical effect. The aim of this study was to determine whether MRI signal intensity (SI) was correlated to the consistency or blood supply of pituitary macroadenoma. METHODS Forty eight pituitary macroadenoma patients were underwent preoperative(More)
INTRODUCTION The difficulty of predicting the efficacy of somatostatin analogs (SSA) is not fully resolved. Here, we quantitatively evaluated the predictive value of relative signal intensity (rSI) on T1- and T2-weighted magnetic resonance imaging (MRI) for the short-term efficacy (3 months) of SSA therapy in patients with active acromegaly and assessed the(More)
BACKGROUND We aim to study surgical technique and analyze the related factors affecting tumor total removal and postoperative endocrinological remission for endoscopic endonasal pituitary adenomas surgery. METHODS We retrospectively analyzed 178 endoscopic endonasal pituitary adenomas surgery from March 2011 to May 2014. Endonasal approach included the(More)